Method and system for delivering information with caching based on interest and significance

ABSTRACT

A method ( 200 ) for delivering information (for example, monitoring data) is proposed. The information is collected ( 235 ) on a central server ( 110 ) from remote sources ( 105 ), in order to be provided to multiple clients ( 120 ) in response to corresponding requests. In the method of the invention, an interest index is calculated ( 280 ) according to the number of preceding requests of the information that have been submitted in the past (so as to estimate the interest of the clients for the information); moreover, a significance index is calculated ( 220 ) according to a probability of a current value of the information that is uploaded onto the server by the corresponding source (so as to estimate its importance for the clients). A frequency for refreshing the information on the server can then be determined ( 245 ) according to both the interest index and the significance index. In this way, the refresh frequency self-adapts to the expected behavior of the clients.

TECHNICAL FIELD

The present invention relates to the data processing field. Morespecifically, the present invention relates to the delivering ofinformation in a data processing system.

BACKGROUND ART

Data processing systems are routinely used to deliver information ininteractive applications (wherein the information is typically displayedon a monitor in real-time). Particularly, in a system with distributedarchitecture the required information is provided by one or more remotesource computers. In this case, the information is typically collectedon a central server computer (from the different source computers);multiple client computers can then download the information from theserver computer when it is necessary. A typical example is a monitoringapplication (such as the “IBM Tivoli Monitoring, or ITM”), whereinmonitoring data indicative of the performance of different managedcomputers is measured on each one of them; the monitoring data is thencollected on the server computer, where it is available for downloadingby one or more operators. This allows the operators to track the healthand performance of the system; for example, the operators can detect anycritical condition of the managed computers. In this case, theytypically download further information for analyzing the criticalcondition more in detail and possibly identifying its cause (so as totake corresponding correction actions).

In this context, it is generally untenable to trigger the collection ofthe information from the source computers synchronously (i.e., when acorresponding request is received from every client computer). Indeed,this approach involves a very high response time for the clientcomputers (since each request cannot be satisfied until the collectionof the requested information has been completed).

A solution known in the art is of collecting the information on theserver computer periodically, and then storing it into a cache memory.As a result, the information is immediately available on the servercomputer when it is requested; moreover, next requests for the sameinformation at short intervals can be satisfied by the server computerdirectly without requiring multiple collections from the correspondingsource computers.

A critical aspect of the above-described solution is the choice of arefresh frequency of the information on the server computer. Indeed, atoo low refresh frequency would impair the currency of the informationthat is delivered to the client computers (since the client computersreceive the information as it was when collected from the sourcecomputers ahead of the actual request). Conversely, a too high refreshfrequency would overload the system, with a detrimental impact on itsoverall performance.

Another problem arises when more source computers try to uploadinformation onto the server computer at the same time. As a consequence,contention problems on the server computer can occur. This adverselyaffects the response time of the client computers (especially when theprocessing time required for the collection of the information is notnegligible, and then the server computer might remain busy for a quitelong period).

SUMMARY OF THE INVENTION

According to the present invention, the idea of dynamically updating therefresh frequency of the information is suggested.

Particularly, an aspect of the invention provides a method fordelivering information in a data processing system from a server entityto one or more client entities. The method includes the following stepsfor each of at least one information item. At first, a current value ofthe information item is collected on the server entity from acorresponding source entity according to a corresponding refreshfrequency. The current value of the information item is then deliveredfrom the server entity to each one of the client entities (in responseto a corresponding request). The method further includes the step ofdetermining an interest index of the information item. The interestindex is indicative of an interest of the client entities for theinformation item; this index is determined according to precedingrequests for the information item that have been submitted by the cliententities previously. The refresh frequency of the information item isthen updated according to the corresponding interest index.

The proposed solution allows self-tuning the refresh frequency, so as toadapt it to the expected behavior of the client entities. For example,the refresh frequency can be increased for information that is likely tobe requested at short intervals, whereas it can be reduced forinformation that is of less interest.

Particularly, the refresh frequency is based on the interest that hasbeen demonstrated by the client entities in the past (and it is thenlikely to apply to the near future as well).

This provides a high currency of the information when it is actuallynecessary; at the same time, the workload of the system is optimized(since the refresh of the information is delayed when it is lessuseful).

Moreover, the refresh frequencies of the information provided by theseveral source entities will be generally different. This stronglyreduces the risk of having any contention on the server entity for thecollections of the information (since they generally occur in acompletely asynchronous manner).

The different embodiments of the invention described in the followingprovide additional advantages.

For example, in a preferred embodiment the refresh frequency alsodepends on a significance index of the information item; this indexrepresents a significance of the current value of the information itemfor the client entities, and it is determined according to itsinformation content.

The proposed feature completes the solution by better adapting therefresh frequency to the actual behavior of the client entities that islikely to occur; for example, the refresh frequency can be increased forinformation that is very important (and then it is likely to berequested shortly), whereas it can be reduced for information that is ofless value.

A suggested choice for determining the interest index is of calculatingit according to a number of the preceding requests for the informationitem (being submitted by the client entities in a predetermined period).

This algorithm allows estimating the interest that has been demonstratedby the client entities for the information in the past in a very simplemanner.

In a specific implementation of the invention, the significance index isdetermined by classifying the current value of the information item intoa corresponding category (to which a predefined significance index hasbeen associated).

The proposed algorithm provides the desired result with a very lowcomputation complexity.

Alternatively, the significance index can be based on a probability thatis estimated for the current value of the information item (according toa set of preceding values thereof).

This choice improves the accuracy of the solution (with a slightlyincrease of its complexity); moreover, the process now dynamicallyself-adapts to the different values of the information that is actuallycollected.

Preferably, the significance index is determined on the source entity,and it is then transmitted to the server entity together with thecorresponding information item; on the other hand, the refresh frequencyis updated on the server entity accordingly and returned to the sourceentity.

As a result, the operations relating to the determination of thesignificance indexes (being peculiar for each information item) aredistributed throughout the source entities, so as to prevent overloadingthe server entity; at the same time, the common operations relating tothe determination of the interest indexes are centralized on the serverentity (taking advantage of the direct availability of the statisticsdata that might be necessary).

As an additional enhancement, the refresh frequency of the informationitem is modulated according to a substantially random value.

This further reduces the risk of contention on the server entity.

A further aspect of the present invention provides a computer programfor performing the above-described method.

A still further aspect of the invention provides a program productembodying this computer program.

Another aspect of the invention provides a corresponding data processingsystem.

The characterizing features of the present invention are set forth inthe appended claims. The invention itself, however, as well as furtherfeatures and advantages thereof will be best understood by reference tothe following detailed description, given purely by way of anonrestrictive indication, to be read in conjunction with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 a is a schematic block diagram of a data processing system inwhich the solution according to an embodiment of the invention isapplicable;

FIG. 1 b shows the functional blocks of an exemplary computer of thesystem;

FIG. 2 depicts the main software components that can be used forpracticing the solution according to an embodiment of the invention;

FIGS. 3 a-3 b show a diagram describing the flow of activities relatingto an implementation of the solution according to an embodiment of theinvention; and

FIG. 4 is a timing diagram of an exemplary operation of the system.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT(S)

With reference in particular to FIG. 1 a, a data processing system 100with distributed architecture is illustrated. The system 100 includesmultiple source computers 105, each one providing correspondinginformation. The information is collected (from the different sourcecomputers 105) on a central server computer 110. The server computer 110communicates with an interface computer 115. The interface computer 115delivers the collected information to multiple client computers 120 ondemand.

For example, the system 100 runs a monitoring application that is usedto trace operation of the source computers 105 (representing theentities that are managed in the monitoring application); in this case,the information consists of monitoring data of the source computers 105.Typically, the information provided to the client computers 120 isdisplayed on a console of an operator; this allows the operator tomonitor the health and performance of the system 100.

As shown in FIG. 1 b, a generic computer of the system (source computer,server computer, interface computer, or client computer) is denoted with150. The computer 150 is formed by several units that are connected inparallel to a system bus 153. In detail, one or more microprocessors(μP) 156 control. operation of the computer 150; a RAM 159 is directlyused as a working memory by the microprocessors 156, and a ROM 162stores basic code for a bootstrap of the computer 150. Peripheral unitsare clustered around a local bus 165 (by means of respectiveinterfaces). Particularly, a mass memory consists of a hard disk 168 anda drive 171 for reading CD-ROMs 174. Moreover, the computer 150 includesinput devices 177 (for example, a keyboard and a mouse), and outputdevices 180 (for example, a monitor and a printer). A Network InterfaceCard (NIC) 183 is used to connect the computer 150 to a network. Abridge unit 186 interfaces the system bus 153 with the local bus 165.Each microprocessor 156 and the bridge unit 186 can operate as masteragents requesting an access to the system bus 153 for transmittinginformation. An arbiter 189 manages the granting of the access withmutual exclusion to the system bus 153.

Moving now to FIG. 2, the main software components that run on theabove-described system are denoted as a whole with the reference 200.The programs and the data are typically stored on the hard disks andloaded (at least partially) into the working memories of the computerswhen the programs are running. The programs are initially installed ontothe hard disks from CD-ROMs.

Considering in particular a generic source computer 105, a module 205generates a current value of the relevant information. In the example atissue, the generator 205 measures performance parameters of differenthardware and/or software resources of the source computer 105 (forexample, a processing power consumption, a memory space usage, abandwidth occupation, and the like); monitoring data is then derivedfrom those performance parameters (either directly or after an analysisthereof).

The generator 205 is activated continually according to a correspondingrefresh frequency, which is stored in a file 210. The information soobtained is saved into a local log 215. The log 215 is accessed by ananalyzer 220. As described in detail in the following, the analyzer 220determines a significance index of the information; this indexrepresents the (alleged) significance of the current value of theinformation for the client computers. For this purpose, the analyzer 220can access two different databases 222 and 225. The database 222 storesthe definition of a set of (disjoint) categories for the information,together with corresponding predefined significance indexes. Thecategories are defined by properties (or attributes) of the values ofthe information; for example, the categories identify a low, a standard,a high, a critical and a severe workload of the source computer 105(each one defined by a corresponding range of values). On the otherhand, the database 225 stores statistics data of preceding values of theinformation (which statistics data is updated by the analyzer 220itself); for example, the database 225 includes the runningprobabilities for predefined ranges of values of the information.

An agent 230 receives the current value of the information (from thegenerator 205) and the corresponding significance index (from theanalyzer 220). The agent 230 uploads the current value of theinformation and its significance index onto the server computer 110(according to the refresh frequency); the agent 230 also receives a newrefresh frequency from the server computer 110, and stores it into thecorresponding file 210 (overriding its preceding value).

The current value of the information and its significance index arereceived by a collector 235 (running on the server computer 110); inthis way, the source computer 105 and the server computer 110 operateaccording to a push paradigm (wherein the information is transmitted bythe agent 230 of its own motion according to the refresh frequency). Thecurrent value of each information item collected by the module 235 (fromthe different source computers of the system) is stored into a cachememory 240 (replacing its preceding value).

At the same time, the collector 235 provides the significance index (ofthe information that has just been received) to a predictor 245. As itwill be apparent in the following, the predictor 245 calculates the newrefresh frequency of the information. The operation is based on thesignificance index (received from the collector 235) and on an interestindex (which is extracted from a corresponding repository 250); thisfurther index represents the interest that has been demonstrated in thepast (and it is then likely to apply to the near future as well) by theclient computers for the information. The predictor 245 also receives amodulation value from a module 255, and updates the refresh frequencyaccordingly. The new refresh frequency so obtained is then returned tothe collector 235 (so as to be transmitted to the corresponding sourcecomputer 105).

The cache memory 240 is accessed by a dispatcher 260. The dispatcher 260communicates with a web server 265 running on the interface computer115. The module 265 exposes a web interface, which is accessed by eachclient computer 120 through a corresponding browser 270. The web server265 bridges between the browser 270 and the dispatcher 260.Particularly, the web server 265 allows the client computer 120 tosubmit requests for a desired information item; in response thereto, thedispatcher 260 extracts the available value of the information from thecache memory 260 and delivers it to the client computer 120.

The dispatcher 260 also maintains a database 275, which storesstatistics data of the received requests; for example, for eachinformation item the database 275 includes the number of precedingrequests that have been submitted by all the client computers of thesystem in a predetermined period (for example, the last 1-5 minutes).The database 275 is accessed by an estimator 280. As described in detailin the following, the estimator 280 determines a new interest index ofthe information that has just been requested; the new interest index soobtained is stored into the corresponding repository 250 (replacing itspreceding value).

Considering now FIGS. 3 a-3 b, the logic flow of a monitoring processthat can be implemented in the above-described system is representedwith a method 300. The method starts at block 303 (in the swim-lane of ageneric source computer) as soon as a period corresponding to therefresh frequency expires; in response thereto, a current value of therelevant information is generated. The flow of activity then branches atblock 306 according to a configuration of the source computer. If thesource computer operates in a static mode, the blocks 309-312 areexecuted, whereas if the source computer operates in a dynamic mode theblocks 315-321 are executed; in both cases, the method merges at block324.

Considering now block 309 (static mode), the current value of theinformation is classified into one of the available categories; in theexample at issue, the monitoring data is compared with the predefinedranges for its value (so as to determine whether it is indicative of alow, a standard, a high, a critical or a severe workload of the sourcecomputer). Continuing to block 312, the method assigns the significanceindex associated with the determined category to the current value ofthe information. Typically, the significance index is set to low values(such as from 0.5 to 1) for categories relating to standard situations;conversely, the significance index is set to high values (such as from 1to 1.5) for categories relating to anomalous situations; moreover, it isset to far higher values (such as from 1.5 to 2) for categories relatingto dangerous situations that would require a prompt attention.

With reference instead to block 315 (dynamic mode), the probability ofthe current value of the information is estimated (according to theavailable statistics data of the preceding values thereof). Thesignificance index of the information is then calculated at block 318from the probability of its current value; for example, denoting with Isthe significance index and with Pc the probability of the current valueof the information, we can have:Is=2−1.5−PcIn this way, the significance index takes low values for highprobabilities (i.e., standard situations), down to Is=0.5 for Pc=1;conversely, the significance index takes high values for lowprobabilities (i.e., anomalous or dangerous situations), up to Is=2 forPc=0. The method then passes to block 321, wherein the runningprobabilities of the values of the information (in the correspondingdatabase) are updated according to the current value that has just beengenerated.

Moving now to block 324, the current value of the information and thecorresponding significance index are uploaded onto the server computer.The flow of activity then proceeds to block 327 in the swim lane of theserver computer, wherein the current value of the information is storedinto the corresponding cache memory. The new refresh frequency for theinformation is calculated at block 330 (according to the correspondingsignificance index and interest index); for example, denoting the fr therefresh frequency and with Ii the interest index, we can have:fr=Is·IiAs it will be evident in the following, the interest index represents afrequency value (for the refresh of the information); on the other hand,the above-described significance index represents an adjusting factor(ranging from 0.5 to 2 in the example at issue). Therefore, the interestindex substantially defines the desired refresh frequency; thesignificance index changes the refresh frequency by decreasing it forvalues lower than 1 (relating to information being not particularlyvaluable) or by increasing it for values higher than 1 (relating toinformation being very valuable).

The method continues to block 333, wherein the refresh frequency isupdated according to the modulation value. Preferably, the modulationvalue consists of a pseudo-random number (for example, ranging from −0.1to +0.1); in this case, the refresh frequency is decreased or increasedby a corresponding fraction, that is (denoting with M the modulationvalue):fr=fr+M·frAs a result, the refresh frequency is modulated around the desired value(at most of ±10% in the example at issue); this provides a randomscattering of the refresh frequency, thereby decorrelating the operationof any multiple source computers providing the same information (andthen with the same refresh frequency).

The new refresh frequency so obtained is returned to the source computerat block 336. In response thereto, the source computer at block 339stores the new refresh frequency into the corresponding file. The flowof activity then goes back to block 303 as soon as the (new) refreshperiod expires, so as to reiterate the above described operations.

At the same time (in a completely asynchronous way), a generic clientcomputer submits a request of an information item to the interfacecomputer at block 342. The interface computer forwards the request tothe server computer at block 345. Moving now to the swim-lane of theserver computer, the flow of activity forks into two branches that areexecuted concurrently.

Considering in particular block 348, the server computer retrieves theavailable value of the desired information from the cache memory. Theinformation so obtained is immediately returned to the interfacecomputer at block 351. The interface computer in turn relays theinformation to the client computer at block 354. As a result, theinformation can be displayed on the client computer at block 357.

At the same time (at block 360 in the swim-lane of the server computer),the number of the preceding requests that have been submitted for thesame information by all the client computers (in the last 1-5 minutes inthe example at issue) is updated accordingly in the correspondingdatabase. Considering now block 363, the interest index of theinformation is calculated as a function of the number of the precedingrequests; for example, denoting with n the number of the precedingrequests, with L a minimum frequency and with H a maximum frequency (forexample, ls and 60 s, respectively), we can apply the following formula:Ii=H−(H−L)·e ^(−n)In this way, when n=0 the interest index takes its lowest value(Ii=H−H+L=L), whereas when n→∞ the interest index takes its highestvalue (Ii=H−0=H). This leads (being fr=Is·Ii) to a decrease of therefresh frequency for low numbers of the preceding requests (since theinformation is not of particular interest) and to an increase of therefresh frequency for high numbers of the preceding requests (since theinformation is very interesting).

The two branches then joint by returning to block 342 (in the swim-laneof the client computer). In this way, the same operationsdescribed-above are repeated as soon as a further request of informationis submitted by the client computer.

A timing diagram relating to an exemplary operation of theabove-described system is illustrated in FIG. 4. In this case, theuploads of the information from a generic source computer onto theserver computer are denoted with 405; the corresponding requests thatare submitted by the different client computers are instead denoted with410.

As can be seen, in a normal situation the information is uploaded ontothe server computer with a relatively low refresh frequency fr₁ (enoughto satisfy the requests that are routinely submitted by the clientcomputers). However, as soon as information of particular interest isgenerated by the source computer, the refresh frequency is increasedaccordingly (fr₂). In this way, up-to-date information is alreadyavailable on the server computer for the high number of requests thatwill be submitted by the client computers. Once the situation returns tothe normality, the refresh frequency returns to its previous value fr₁.

For example, in the monitoring application at issue the operators trackthe performance of the system every minute (so that a refresh frequencyof 30 s is acceptable). However, when a problem arises they startdownloading information with a very high frequency (such as every 1-5s), in order to analyze the problem and possibly solve it. In thissituation, a real time response of the system is of the utmostimportance (for example, with a refresh frequency of ls), so as to allowthe operators to evaluate the result of any correction action that hasbeen enforced. Once the problem has been fixed, the situation returns tothe normality.

Naturally, in order to satisfy local and specific requirements, a personskilled in the art may apply to the solution described above manymodifications and alterations. Particularly, although the presentinvention has been described with a certain degree of particularity withreference to preferred embodiment(s) thereof, it should be understoodthat various omissions, substitutions and changes in the form anddetails as well as other embodiments are possible; moreover, it isexpressly intended that specific elements and/or method steps describedin connection with any disclosed embodiment of the invention may beincorporated in any other embodiment as a general matter of designchoice.

For example, the reference to the monitoring application is merelyillustrative and must not be interpreted in a limitative manner; indeed,the solution of the invention can be used to deliver news provided bypress agencies, stock exchange data provided by multiple sites, and thelike.

Similar considerations apply if the system has a different structure orincludes equivalent components; moreover, the system can be based on anynumber of source computers and/or client computers (down to a singleone), or the client computers can access the server computer directly(without any interface computer). Likewise, each computer can haveanother structure or it can be replaced with any data processing entity(such as a PDA, a mobile phone, and the like). Alternatively, the sameinformation item can be provided by two or more source computers, oreach source computer can generate two or more information itemsindependently.

It should be noted that although the solution of the invention isspecifically designed for a system working according to the pushparadigm, the use of the devised solution in other environments is notexcluded.

In any case, the numerical examples described above are merelyillustrative and must not be interpreted in a limitative manner.

The principles of the invention should not be limited to the proposedformula for calculating the refresh frequency (and to the proposed typesof significance index and/or interest index); for example, both indexescan be expressed as a time and a refresh period can be defined by theirmean-square value, or the two indexes can be used to update a precedingvalue of the refresh frequency according to a predefined policy.

Moreover, other formulas for calculating the interest index are withinthe scope of the invention (for example, based on a hyperbolic law).

The concepts of the present invention are also applicable when differentcategories of information are taken into account (down to only two, forexample, defined by the reaching of a threshold value by the monitoringdata).

Alternative formulas for calculating the significance index from theprobability of the current value of the information are alsocontemplated (such as based on its logarithm).

Likewise, the refresh frequency can be modulated in an equivalent way(for example, using a barrel-shift algorithm or a modulator of higherorder).

In any case, the programs on the different computers can be structuredin another way, or additional modules or functions can be provided;likewise, the different memory structures can be of different types, orcan be replaced with equivalent entities (not necessarily consisting ofphysical storage media). Alternatively, the proposed solution canimplement an equivalent method involving similar or additional steps.

Moreover, it will be apparent to those skilled in the art that theadditional features providing further advantages are not essential forcarrying out the invention, and may be omitted or replaced withdifferent features.

For example, an implementation wherein the refresh frequency is based onthe interest index only is within the scope of the invention.Vice-versa, it is expressly intended that the determination of therefresh frequency according to the significance index only is notexcluded.

Alternatively, the interest index can be calculated from differentstatistics parameters characterizing a distribution of the precedingrequests, or from any other indicator of an interest that have beendemonstrated for the information by the client computers in the past.

Likewise, it is possible to determine the significance index of thecurrent value of the information from any other indicator of thecorresponding information content (for example, based on its entropy,quality, detail, and the like); alternatively, the significance indexcan also be set manually (such as for the news).

Without departing from the principles of the invention, the significanceindex can be calculated on the server computer and/or the refreshfrequency can be calculated on each source computer directly.

Moreover, an implementation without any modulation of the refreshfrequency is contemplated.

In any case, the programs can be distributed in any other computerreadable medium (such as a DVD).

At the end, the method according to the present invention leads itselfto be carried out with a hardware structure (for example, integrated inchips of semiconductor material), or with a combination of software andhardware.

1. A method (300) for delivering information in a data processing systemfrom a server entity to at least one client entity, wherein for each ofat least one information item the method includes the steps of:collecting a current value of the information item on the server entityfrom a corresponding source entity according to a corresponding refreshfrequency, delivering the current value of the information item from theserver entity to each of the at least one client entity in response to acorresponding request, characterized by the steps of determining aninterest index of the information item, being indicative of an interestof the at least one client entity for the information item, according topreceding requests for the information item being submitted by the atleast one client entity previously, and updating the refresh frequencyof the information item according to the corresponding interest index.2. The method according to claim 1, further including the steps of:determining a significance index of the information item, beingindicative of a significance of the current value of the informationitem for the at least one client entity, according to an informationcontent of the current value of the information item, and updating therefresh frequency of the information item according to the correspondingsignificance index.
 3. The method according to claim 1, wherein the stepof determining the interest index of the information item includes:storing an indication of a number of the preceding requests for theinformation item being submitted by the at least one client entity in apredetermined period, and calculating the interest index according tosaid number.
 4. The method according to claim 2, wherein the step ofdetermining the significance index of the information item includes:classifying the current value of the information item into one of aplurality of categories, each category being associated with apredefined significance index, and assigning the predefined significanceindex associated with the category to the information item.
 5. Themethod according to claim 2, wherein the step of determining thesignificance index of the information item includes: estimating aprobability of the current value of the information item according to aset of preceding values of the information item being collectedpreviously, and calculating the significance index according to saidprobability.
 6. The method according to claim 2, wherein the methodfurther includes the steps under the control of the corresponding sourceentity of: generating the current value of the information itemaccording to the corresponding refresh frequency, determining thesignificance index of the information item, and transmitting the currentvalue of the information item and the corresponding significance indexto the server entity, and the steps under the control of the serverentity of: caching the current value of the information item, updatingthe refresh frequency of the information item according to thecorresponding interest index and significance index, and returning therefresh frequency of the information item to the source entity.
 7. Themethod according to claim 1, further including the step of: modulatingthe refresh frequency of the information item according to asubstantially random modulation value.
 8. A computer program in acomputer readable medium directly loadable into a working memory of adata processing system for performing the method when the program is runon the system comprising the steps of: collecting a current value of theinformation item on the server entity from a corresponding source entityaccording to a corresponding refresh frequency, delivering the currentvalue of the information item from the server entity to each of the atleast one client entity in response to a corresponding request,characterized by the steps of determining an interest index of theinformation item, being indicative of an interest of the at least oneclient entity for the information item, according to preceding requestsfor the information item being submitted by the at least one cliententity previously, and updating the refresh frequency of the informationitem according to the corresponding interest index.
 9. (canceled)
 10. Adata processing system including a server entity, at least one cliententity, means for collecting a current value of each of at least oneinformation item on the server entity from a corresponding source entityaccording to a corresponding refresh frequency, and means for deliveringthe current value of the information item from the server entity to eachof the at least one client entity in response to a correspondingrequest, characterized in that the system further includes means fordetermining an interest index of the information item, being indicativeof an interest of the at least one client entity for the informationitem, according to preceding requests for the information item beingsubmitted by the at least one client entity previously, and means forupdating the refresh frequency of the information item according to thecorresponding interest index.